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  "name": "",
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  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#Sacramento Reach Fitting Example\n",
      "\n",
      "This notebook shows the end-to-end reach fitting machinery using simulated SWOT data for the Sacramento River. It illustrates how to use the width data\n",
      "stored in a database to restrict the maximum width separately at each river node.\n",
      "\n",
      "Below are the Python modules developped for fitting SWOT data over the each:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as N\n",
      "from SWOTRiver import SWOTL2\n",
      "from SWOTRiver import ReachExtractor\n",
      "from SWOTRiver import RiverObs\n",
      "from SWOTRiver import FitRiver\n",
      "from SWOTRiver import WidthDataBase\n",
      "\n",
      "# For plotting\n",
      "\n",
      "%pylab inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Populating the interactive namespace from numpy and matplotlib\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "WARNING: pylab import has clobbered these variables: ['step']\n",
        "`%matplotlib` prevents importing * from pylab and numpy\n"
       ]
      }
     ],
     "prompt_number": 29
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Read the simulation data\n",
      "\n",
      "In this step, the data are read, a projection to (x,y) coordinates is defined, and the data bounding box is found.\n",
      "\n",
      "The data locations are given below:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# This is the file for the width data base\n",
      "\n",
      "width_db_dir = '/Volumes/Reservoir/Data/GWD-LR/nAmerica_GRWDL/'\n",
      "width_db_file = width_db_dir+'nAmerica_GRWDL.h5'\n",
      "\n",
      "# This is the SWOT data\n",
      "\n",
      "data_dir = '/Volumes/Reservoir/Data/SWOT/'\n",
      "l2_file = (data_dir +\n",
      "'swot_intf_line2-9_cycle_0001_pass_0014_w0.23_15dB_dem0.1slp.RightSwath.nc')\n",
      "\n",
      "# This is the file for the reach data base\n",
      "\n",
      "db_dir = '../../data/nAmerica_GRWDL_river_topo/'\n",
      "shape_file_root = db_dir+'nAmerica_GRWDL_river_topo'"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 30
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "For this example, only data with classification=1 labels are used (pure water pixels) and the latitude and longitude are assumed to be known from the reference interferogram."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "class_list=[1]\n",
      "lat_kwd='no_layover_latitude'\n",
      "lon_kwd='no_layover_longitude'\n",
      "\n",
      "l2 = SWOTL2(l2_file,class_list=class_list,lat_kwd=lat_kwd,lon_kwd=lon_kwd)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Dataset opened\n",
        "Bounding box calculated\n",
        "Good data selected\n",
        "lat/lon read"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "projection set and x,y calculated\n"
       ]
      }
     ],
     "prompt_number": 31
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The heights to be used are the noisy height and the water_height, the true height weighted by the radar response."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "h = l2.get('height')\n",
      "htrue = l2.get('water_height')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 32
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#Extract the river reaches overlapping the data bounding box\n",
      "\n",
      "In this case, the reaches are from the North America Global River Width Database for Large Rivers. The data were made by [Tamlin Pavelsky](mailto:pavelsky@unc.edu) and [George Allen](mailto:georgehenryallen@gmail.com) and modified by [Ernesto Rodriguez](mailto:ernesto.rodriguez@jpl.nasa.gov) so that reaches appeared as topologically connected. The results are in the shapefile *nAmerica_GRWDL_river_topo.shp*.\n",
      "\n",
      "The next step scans through the database and finds all of the overlapping reaches in the data base (only one is found). A small buffer of about 2km is placed about the data bounding box to make sure the river is not cut."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "clip_buffer = 0.02\n",
      "reaches = ReachExtractor(shape_file_root, l2,clip_buffer=clip_buffer)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 33
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The following step prints out the reach index and metadata:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print 'Reach indexes:',reaches.reach_idx\n",
      "print 'Metadata:'\n",
      "reaches[0].metadata"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Reach indexes: [704]\n",
        "Metadata:\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 34,
       "text": [
        "{'break_idx': 1388940,\n",
        " 'latmax': 40.03200149536133,\n",
        " 'latmin': 38.16350173950195,\n",
        " 'lonmax': -121.5009994506836,\n",
        " 'lonmin': -122.11900329589844,\n",
        " 'npoints': 10144,\n",
        " 'reach': 375745.03125,\n",
        " 'width_max': 532.0,\n",
        " 'width_mean': 115.74655151367188,\n",
        " 'width_min': 30.0,\n",
        " 'width_std': 52.802425384521484}"
       ]
      }
     ],
     "prompt_number": 34
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#Extract the width information for this reach from the width database"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "width_db = WidthDataBase(width_db_file)\n",
      "\n",
      "max_width = width_db.get_river(reaches.reach_idx[0],\n",
      "                                      columns=['width'],\n",
      "                             asarray=True,transpose=False,\n",
      "                             bounding_box=l2.bounding_box,\n",
      "                             clip_buffer=clip_buffer)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 35
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print 'max_width length:',len(max_width)\n",
      "print 'x length:',len(reaches[0].x)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "max_width length: 1915\n",
        "x length: 1915\n"
       ]
      }
     ],
     "prompt_number": 36
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#Compute the center line and associate observations with it\n",
      "\n",
      "In the following step, the centerline is computed along the extracted reach, but the nodes of the centerline are interpolated to be placed every ds=50m. The centerline consists of a set of nodes, each of which has a geolocation and associated data. \n",
      "\n",
      "After computing the center line, all points more than max_width/2 away from the centerline are removed. In addition, if a node contains fewer than minobs, it is not considered."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#max_width = 400.\n",
      "ds = 50.\n",
      "minobs = 10\n",
      "river_obs = RiverObs(reaches[0],l2.x,l2.y,\n",
      "                     ds=ds,max_width=max_width,minobs=minobs) "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Centerline initialized\n",
        "Local coordiantes calculated"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      }
     ],
     "prompt_number": 37
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print 'max_width length:',len(river_obs.max_width)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "max_width length: 1506\n"
       ]
      }
     ],
     "prompt_number": 38
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Plot the maximum width along the channel:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "len(river_obs.max_width) == len(river_obs.centerline.x)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 39,
       "text": [
        "True"
       ]
      }
     ],
     "prompt_number": 39
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "figsize(5,5)\n",
      "scatter(river_obs.centerline.x/1.e3,river_obs.centerline.y/1.e3,\n",
      "        c=river_obs.max_width,\n",
      "        edgecolor='none',alpha=0.1,\n",
      "        vmin=0,vmax=300)\n",
      "colorbar(label='Width');"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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/+Zv86Ec/4uabb+bxxx8/67yz+QSoWQnFhoYG+vv7aWxspK+vj/r6+rPOd3oo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\n9lIAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x11ea399d0>"
       ]
      }
     ],
     "prompt_number": 40
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "In the following step, the height and true heights are associated with the nodes:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "river_obs.add_obs('htrue',htrue)\n",
      "river_obs.add_obs('h',h)\n",
      "river_obs.load_nodes(['h','htrue'])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 41
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Get some rough statistics of the differences in heights for the data associated with each node:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "hn_mean = N.array(river_obs.get_node_stat('mean','h'))\n",
      "hn_median = N.array(river_obs.get_node_stat('median','h'))\n",
      "hstdn = N.array(river_obs.get_node_stat('stderr','h'))\n",
      "htn = N.array(river_obs.get_node_stat('mean','htrue'))\n",
      "sn = N.array(river_obs.get_node_stat('mean','s'))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 42
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ave = N.mean(hn_mean - htn)*100\n",
      "err = N.std(hn_mean - htn)*100\n",
      "print 'Mean statitics:   average: %.1f cm std: %.1f cm'%(ave,err)\n",
      "\n",
      "ave = N.mean(hn_median - htn)*100\n",
      "err = N.std(hn_median - htn)*100\n",
      "print 'Median statitics: average: %.1f cm std: %.1f cm'%(ave,err)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Mean statitics:   average: 4.2 cm std: 70.1 cm\n",
        "Median statitics: average: 4.3 cm std: 71.4 cm\n"
       ]
      }
     ],
     "prompt_number": 43
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Plot the distances from the points to the nodes, and the cross-river normal coordinate:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "figsize(10,5)\n",
      "subplot(1,2,1)\n",
      "hist(river_obs.d,bins=100,log=False)\n",
      "xlabel('Distance to node (m)')\n",
      "ylabel('N obserwations')\n",
      "grid();\n",
      "subplot(1,2,2)\n",
      "hist(river_obs.n,bins=100,log=False)\n",
      "xlabel('Normal coordinate (m)')\n",
      "ylabel('N obserwations')\n",
      "grid();"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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1ctORpnucAuB9Tol0gO0aEelZu8Omly5dwtVXX61WPh7Teti05XM83E2kPG+G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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x11eac59d0>"
       ]
      }
     ],
     "prompt_number": 44
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Plot the river geometry, number of observations per node, height vs true height, and a plot of height vs the reach distance downriver."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "figsize(10,10)\n",
      "subplot(2,2,1)\n",
      "idx = river_obs.populated_nodes\n",
      "plot(river_obs.centerline.x[idx]/1.e3,river_obs.centerline.y[idx]/1.e3,\n",
      "     '.',alpha=0.5)\n",
      "xlabel('x (km)')\n",
      "ylabel('y (km)')\n",
      "subplot(2,2,2)\n",
      "idx = river_obs.populated_nodes\n",
      "plot(river_obs.centerline.s[idx]/1.e3,river_obs.nobs[idx],'o',alpha=0.5)\n",
      "grid()\n",
      "xlabel('Reach (km)')\n",
      "ylabel('Number of observations')\n",
      "subplot(2,2,3)\n",
      "plot(htrue,h,'.',alpha=0.01)\n",
      "plot([-10,60],[-10,60],'--k',alpha=0.5)\n",
      "xlim(-10,60)\n",
      "ylim(-10,60)\n",
      "grid()\n",
      "xlabel('h true (m)')\n",
      "ylabel('h measured (m)')\n",
      "subplot(2,2,4)\n",
      "plot(river_obs.s/1.e3,river_obs.htrue,'.',alpha=0.1)\n",
      "plot(river_obs.s/1.e3,river_obs.h,'.',alpha=0.05)\n",
      "grid()\n",
      "xlabel('Reach (km)')\n",
      "ylabel('Height (m)');"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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OzNtb1Z3NnAlffw233gpeXlBdrYY+uzKBZPnLdcuWLcyaNYvhw4d33ZsLlxUX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\nvWmczmvp7e3j/vu3snLlVSSTN7Nv31kE4e6StdS7Td2+k2JZMxB4gHP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1AAAg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ARxwMZwg0axwUpfLC9IkiTyNDOhTUu9lF7Q43j7OJZicWPjRmzNZnu8ja3ZZGZGySqdG6Xm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\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       "text": [
        "<matplotlib.figure.Figure at 0x11e78c990>"
       ]
      }
     ],
     "prompt_number": 45
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Plot the true river height averaged over each node, and the measured height, similarly averaged for mean and median averaging. The gray lines are 2 standard errors away from the truth."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "figsize(10,5)\n",
      "subplot(1,2,1)\n",
      "plot(sn/1.e3,htn,'.',alpha=0.1)\n",
      "plot(sn/1.e3,hn_mean,'.',alpha=0.2)\n",
      "plot(sn/1.e3,htn+2*hstdn,'-k',alpha=0.1)\n",
      "plot(sn/1.e3,htn-2*hstdn,'-k',alpha=0.1)\n",
      "xlabel('Reach (km)')\n",
      "ylabel('Height (m)')\n",
      "title('Mean')\n",
      "\n",
      "subplot(1,2,2)\n",
      "plot(sn/1.e3,htn,'.',alpha=0.1)\n",
      "plot(sn/1.e3,hn_median,'.',alpha=0.2)\n",
      "plot(sn/1.e3,htn+2*hstdn,'-k',alpha=0.1)\n",
      "plot(sn/1.e3,htn-2*hstdn,'-k',alpha=0.1)\n",
      "xlabel('Reach (km)')\n",
      "title('Median')\n",
      "ylabel('Height (m)');"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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9iKZqDM4NMhwdrmu3Y1lW7czcpRYWFmr9EV8deZUfj/6Yn134GaZlEo1GNy2x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DzCRPfElvdWLBYBrKXK3eKjfu5FTZjw2LDZbOi6TrVa7VirsTFIut1u6vU69WqdmdQMa8oaA8EB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\njDGiov0AAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x11e80a750>"
       ]
      }
     ],
     "prompt_number": 46
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#Final step: fit the truth and measurements over the sub-reaches\n",
      "\n",
      "The fitting algorithm right now implements three different fitting methods, as described in [StatsModels](http://statsmodels.sourceforge.net):\n",
      "\n",
      "* Ordinary Least Squares (OLS)\n",
      "* Weighted Least Squares (WLS)\n",
      "* Robust Linear Models (RLM)\n",
      "\n",
      "The software will eventually incorporate better outlier rejection at the node level. Right now it has tail trimming, but this is not examined in this example.\n",
      "\n",
      "\n",
      "In the first step, initialize the fitting object with the observations:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fit = FitRiver(river_obs)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 47
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## An example\n",
      "\n",
      "Take the reach between 40km and 50km and fit the measured height and the true height using ordinary unweighted least squares:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "smin = 40.e3\n",
      "smax = 50.e3\n",
      "\n",
      "h_ols_results = fit.fit_linear(smin,smax,'h',fit='OLS')\n",
      "yfit_ols = N.dot(fit.X,h_ols_results.params)\n",
      "h = fit.y\n",
      "\n",
      "htrue_ols_results = fit.fit_linear(smin,smax,'htrue',fit='OLS')\n",
      "htrue = fit.y\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 48
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Get the errors in slope and height, convert to suitable units (cm and cm/km) and print:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "herror = (h_ols_results.params[1] - htrue_ols_results.params[1])*100\n",
      "slp_error = (h_ols_results.params[0] - htrue_ols_results.params[0])*1.e5\n",
      "print('Height error: %.1f cm'%herror)\n",
      "print(r'Slope error:  %.1f cm/km'%slp_error)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Height error: 0.7 cm\n",
        "Slope error:  2.1 cm/km\n"
       ]
      }
     ],
     "prompt_number": 49
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Repeat with weighted least squares:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\n",
      "h_wls_results = fit.fit_linear(smin,smax,'h',fit='WLS')\n",
      "yfit_wls = N.dot(fit.X,h_wls_results.params)\n",
      "\n",
      "htrue_wls_results = fit.fit_linear(smin,smax,'htrue',fit='WLS')\n",
      "\n",
      "herror = (h_wls_results.params[1] - htrue_wls_results.params[1])*100\n",
      "slp_error = (h_wls_results.params[0] - htrue_wls_results.params[0])*1.e5\n",
      "print('Height error: %.1f cm'%herror)\n",
      "print(r'Slope error:  %.1f cm/km'%slp_error)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Height error: 1.3 cm\n",
        "Slope error:  3.1 cm/km\n"
       ]
      }
     ],
     "prompt_number": 50
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Repeat with robust fitting:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "h_rlm_results = fit.fit_linear(smin,smax,'h',fit='RLM')\n",
      "yfit_rlm = N.dot(fit.X,h_rlm_results.params)\n",
      "\n",
      "htrue_rlm_results = fit.fit_linear(smin,smax,'htrue',fit='RLM')\n",
      "herror = (h_rlm_results.params[1] - htrue_rlm_results.params[1])*100\n",
      "slp_error = (h_rlm_results.params[0] - htrue_rlm_results.params[0])*1.e5\n",
      "print('Height error: %.1f cm'%herror)\n",
      "print(r'Slope error:  %.1f cm/km'%slp_error)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Height error: -0.5 cm\n",
        "Slope error:  2.8 cm/km\n"
       ]
      }
     ],
     "prompt_number": 51
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here is a plot of the three solutions:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "figsize(6,6)\n",
      "plot(fit.s/1.e3,htrue,'-',alpha=0.7,linewidth=2,label='Truth')\n",
      "plot(fit.s/1.e3,h,'o',alpha=0.2)\n",
      "plot(fit.s/1.e3,yfit_ols,'-',linewidth=2,label='OLS')\n",
      "plot(fit.s/1.e3,yfit_wls,'-',linewidth=2,label='WLS')\n",
      "plot(fit.s/1.e3,yfit_rlm,'-',linewidth=2,label='RLM')\n",
      "xlabel('Reach (km)')\n",
      "ylabel('Height (m)')\n",
      "grid()\n",
      "legend(loc='best');"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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SFyp/rouYmBjH+vryr/N/MTExLqlrWQpCCOFTqqqqnLq/P0+KczfJAQghhJ+QHIAQQohe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\ngBBC+CkpAEII4af+Hx9IpRa1toEtAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10c3921d0>"
       ]
      }
     ],
     "prompt_number": 52
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##Fitting multiple reaches\n",
      "\n",
      "Now do a more systematic study: start at 30 km reach, and fit successive 10km reaches, displacing each reach by 2.5km. Gather the results and get some statistics. "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "herror_ols = []\n",
      "herror_wls = []\n",
      "herror_rlm = []\n",
      "slp_error_ols = []\n",
      "slp_error_wls = []\n",
      "slp_error_rlm = []\n",
      "\n",
      "smin = 30.e3\n",
      "delta_s = 10.e3\n",
      "smax = smin + delta_s\n",
      "step = 2.5e3\n",
      "sstop = 65.e3\n",
      "\n",
      "while smax <= sstop:\n",
      "    \n",
      "    h_ols_results = fit.fit_linear(smin,smax,'h',fit='OLS')\n",
      "    htrue_ols_results = fit.fit_linear(smin,smax,'htrue',fit='OLS')\n",
      "    herror = (h_ols_results.params[1] - htrue_ols_results.params[1])*100\n",
      "    slp_error = (h_ols_results.params[0] - htrue_ols_results.params[0])*1.e5\n",
      "    herror_ols.append(herror)\n",
      "    slp_error_ols.append(slp_error)\n",
      "    \n",
      "\n",
      "    h_wls_results = fit.fit_linear(smin,smax,'h',fit='WLS')\n",
      "    htrue_wls_results = fit.fit_linear(smin,smax,'htrue',fit='WLS')\n",
      "    herror = (h_wls_results.params[1] - htrue_wls_results.params[1])*100\n",
      "    slp_error = (h_wls_results.params[0] - htrue_wls_results.params[0])*1.e5\n",
      "    herror_wls.append(herror)\n",
      "    slp_error_wls.append(slp_error)\n",
      "    \n",
      "    h_rlm_results = fit.fit_linear(smin,smax,'h',fit='RLM')\n",
      "    htrue_rlm_results = fit.fit_linear(smin,smax,'htrue',fit='RLM')\n",
      "    herror = (h_rlm_results.params[1] - htrue_rlm_results.params[1])*100\n",
      "    slp_error = (h_rlm_results.params[0] - htrue_rlm_results.params[0])*1.e5\n",
      "    herror_rlm.append(herror)\n",
      "    slp_error_rlm.append(slp_error)\n",
      "    \n",
      "    smin += step\n",
      "    smax += step\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 53
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "**Results for Ordinary Least Squares:**"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print('Number of sub-reaches: %d\\n'%len(herror_ols))\n",
      "herror_ave = N.mean(herror_ols)\n",
      "herror_std = N.std(herror_ols)\n",
      "print('Mean height error: %.1f cm'%herror_ave)\n",
      "print(' STD height error: %.1f cm'%herror_std)\n",
      "\n",
      "slp_error_ave = N.mean(slp_error_ols)\n",
      "slp_error_std = N.std(slp_error_ols)\n",
      "print(' Mean slope error: %.1f cm/km'%slp_error_ave)\n",
      "print('  STD slope error: %.1f cm/km'%slp_error_std)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Number of sub-reaches: 11\n",
        "\n",
        "Mean height error: 3.6 cm\n",
        " STD height error: 2.9 cm\n",
        " Mean slope error: 0.2 cm/km\n",
        "  STD slope error: 2.3 cm/km\n"
       ]
      }
     ],
     "prompt_number": 54
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "**Results for Weighted Least Squares:**"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print('Number of sub-reaches: %d\\n'%len(herror_ols))\n",
      "herror_ave = N.mean(herror_wls)\n",
      "herror_std = N.std(herror_wls)\n",
      "print('Mean height error: %.1f cm'%herror_ave)\n",
      "print(' STD height error: %.1f cm'%herror_std)\n",
      "\n",
      "slp_error_ave = N.mean(slp_error_wls)\n",
      "slp_error_std = N.std(slp_error_wls)\n",
      "print(' Mean slope error: %.1f cm/km'%slp_error_ave)\n",
      "print('  STD slope error: %.1f cm/km'%slp_error_std)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Number of sub-reaches: 11\n",
        "\n",
        "Mean height error: 4.5 cm\n",
        " STD height error: 3.6 cm\n",
        " Mean slope error: 0.1 cm/km\n",
        "  STD slope error: 1.8 cm/km\n"
       ]
      }
     ],
     "prompt_number": 55
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "**Results for Robust Linear Model:**"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print('Number of sub-reaches: %d\\n'%len(herror_rlm))\n",
      "herror_ave = N.mean(herror_rlm)\n",
      "herror_std = N.std(herror_rlm)\n",
      "print('Mean height error: %.1f cm'%herror_ave)\n",
      "print(' STD height error: %.1f cm'%herror_std)\n",
      "\n",
      "slp_error_ave = N.mean(slp_error_rlm)\n",
      "slp_error_std = N.std(slp_error_rlm)\n",
      "print(' Mean slope error: %.1f cm/km'%slp_error_ave)\n",
      "print('  STD slope error: %.1f cm/km'%slp_error_std)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Number of sub-reaches: 11\n",
        "\n",
        "Mean height error: 2.5 cm\n",
        " STD height error: 2.8 cm\n",
        " Mean slope error: 0.2 cm/km\n",
        "  STD slope error: 2.3 cm/km\n"
       ]
      }
     ],
     "prompt_number": 56
    }
   ],
   "metadata": {}
  }
 ]
}